Tag Archive : Analytics

How can Inferential Analytics help business with target customers?

Say, you wish to know the average salary of a data scientist professional of a particular region. What are the possible options you can think of?

You personally meet with every data scientist of that region and make a note of his or her salary.

You hand pick few professionals of that region and calculate the average salary.

Although the first method is not impossible, it is a Herculean task indeed, which will consume a lot of resource and time. And keeping in mind the swift moves of companies these days, easy and quick solution is not just preferred but a priority too.

So, what method should be used to figure out the average salary of the data scientist of that area?

The answer is Inferential Statistics.

For starters, and to put it simply for all,Inferential Analytics is typically designed to draw assumptions beyond the present data available.

How it works-By taking a random sample of data from a particular set of population and making assumptions and inferences about the people.

But how can this demographic analysis help a business meet its sales targets? Read on to know more.

How to grow business with Inferential Statistics?

With time, the marketplace shifts and evolves, and so does the list of your clients.

So, it’s time to get ahead of the curve and get a step ahead in the competition-it is time to take the help ofdemographic data, and what better serves the purpose than ‘Inferential Analytics’.

Here are three tips on how you can boost the revenue of your organization by making the most of Inferential Statistics.

Development Plans– Often business leaders plan to expand their company or open a branch at a new location, but how to derive information about the customer base, delivery system, distribution scheduling etc. ?

WithInferential Analytics, you can get key insights on such aspects, coupled with business intelligence reports. Such information is extremely crucial for expansion plans, especially at a new location.

Locate your audience– With the help of Inferential Analytics that examines your current customer data, it is possible to find out where people are most likely going to take benefit out of your product or service. Add to it, you can also narrow down the region where the possibility of customer potential and expansion is high.

Create a marketing campaign– With the help of Inferential Analytics, a business leader can narrow down the branding requirements and focus on specific consumer preferences in a bid to stand out of other competitors in the region. Together with such data, it becomes easy to create a successful marketing campaign.

Grow your business with Inferential Analytics

Expansion of business is nothing less than a big challenge. Not only it takes time and dedication, but also careful location planning. Only with proper location segmentation that helps categorize targeted customers can a business reach its heights.

When the importance of location and population is so impeccable, Inferential Analytics importance cannot be ignored.

If you are blown away by the relevance of Inferential Analytics on business and wish to incorporate it into your company, team members ofSPIN Strategy can be of great help.

It is an inevitable fact and goes without saying that on account of the very nature of data, technology, and analytics that is always at odds for different enterprises, optimal Big Data Deployment strategy may sing a different tune for other business. Period!

This fact-based truth opens the door for strategies, customized only for particular organizations with the pre-conceived motive to deploy Big Data technologies minus any kind of fall out or interruption.

Sounds soothing to the ears?

Note: Before kicking off with the ‘deployment’ process, it comes as a de rigueur step to conduct a detailed evaluation of integration, governance, security, processes, and interoperability, in a bid to reap the pleasure of a seamless Big Data implementation.

Let’s dig deep and get to the pulse of new age Big Data architecture and its deployments know-how for a better understanding.

Age of Big Data Technology

Thanks to our good fortune, we live and breathe in an era of Big Data Analytics, where business enterprises go that extra mile to find ways to harness volumes of unstructured data efficiently.

Business organizations these days take the helping hand from analytics to convert data into valuable insights to pave the way for enhanced operations and informed business decisions.

Riding on the back of intelligent algorithms, organizations give birth to smart data, which can evaluate patterns and signals to help business leaders make informed decisions and thereby cut down costs to perk up profit margins.

However, such an objective is not a walk in the park and requires the assistance of requisite technology within Big Data Environments.

Taking the plunge in the absence of required knowledge and an infallible Big Data strategy is bound to witness a dead-end.

Imperfect deployment road-maps and wrong decisions which can drain out the resources and budget and adversely impact the business performance further gives clarity on the gravity of the situation.

So it is important to understand the Big Data Deployment framework for effective execution.

Big Data Deployment Framework

Out of the lot, there are certain primary factors that manipulate the mammoth decision of employing Big Data technology in a business enterprise.

Such factors include:

• The existence of traditional/non-traditional data in the system
• Presence of low latency data
• Delving into new analytics algorithms
• The requirement for real-time insights

Pillars of Big Data architecture- Analytics, Data, and Technology

Data
There can be no objection to the fact that ‘Data’ is the very heart of technology, analytics, and strategic decision making.

Based on the volume, shape, and latency the type of Big Data technology to be deployed in a company is determined.

Precise mapping of data properties, frequencies, and sources are tagged as significant angles while devising the development strategy.

To make the most of analytics, an amalgamation of traditional technologies and a distributed environment for Big Data can possibly the best road open for some companies to accomplish their business objective.

TechnologyFor most business leaders, it is relatable when we quote that ‘the present infrastructure in many companies is limited to minor data problems’.

Close examination of the existing hardware and software can bridge the gap between tradition and modern approach with ace technologies and predominant systems.

Finally Big Data Integration

The whole idea behind the smooth integration of Big Data technologies in the present infrastructure is to achieve no disruption, zero business downtime, and no cost overruns.

For such integration, numerous databases, nodes, and clusters are required to be explored.

At a business enterprise level, cross-project inter-departmental and multi-platform integration of Big Data technologies must be decided at an early stage, since this can be a difficult task to complete later on.

Concluding Note

Like it or not, a comprehensive, rigorous and importunate decision-making is the absolute need of the hour for deploying Big Data Technologies in any company.

Furthermore, the strategy should make amends with the changing landscape of Big Data technologies.

The deployment strategy is more than a certain piece of information jotted down on a piece of paper.

At SPIN, we understand the mechanism to dispose of Big Data strategy within the present infrastructure of a company in order to bring to pass maximum impact (in a positive way).

Companies that have effectively integrated Predictive Analytics tag Prescriptive Analytics as the next lucrative frontier to approach.

Questions may arise as to how both the terms are inter-linked.

The answer to this lies in the fact that while Predictive Analytics gives a vivid picture of the possible future.

While Prescriptive Analytics reels off how to respond in the best way possible, in tune with the prediction.

How Predictive Analytics exercises its duty?

The first and foremost step of Predictive Analytics is to figure out what are the questions you wish to be answered, based on the past data.

The second step includes figuring out if you have the right data to answer the questions you asked.

The third step includes training your business system to learn everything from your data to forecast outcomes.

Plan your modules

Use your forecasts and insights in your line of business applications for priceless outcomes.

Does your business need Predictive Analytics?

Irrespective of the fact that there are numerous aspects in a business, that needs special attention, Predictive Analytics finds its fit in almost every bit of an organization.

Here are few pointers to start-off with:

Customer Relationship Management (CRM) – Predictive Analytics models can be applied to enterprise applications like CRM, to figure out proper messages to target the customers in the days to come. By predicting the next likely move of the customer, you can spend your messaging dollars effectively.

Marketing- Using Predictive Analytics it is possible to determine the preferences of the customers based on past data and previous history. This will help to predict the future course of action for the company to retain more customers and increase productivity tenfold.

Manage risks- Using Predictive Analytics effectively can help businesses to sketch a roadmap for the company. By predicting future outcomes and possibilities, Predictive Analytics can help organizations to cut down risks significantly.

Let’s start predicting

Companies that have deployed Predictive Analytics in their business operations have flourished beyond expectations, in comparison to the ones who still playing with the thought of it.

Comprehending customers better by tapping on their requirements, and customizing the content as per the needs does wonder for a business, and Predictive Analytics is the key to it.

Well-informed use of Predictive Analytics helps organizations to be aware of market forces and secure their dominance in today’s competitive world.

All in all, predicting the future outcomes guarantees one important fact- substantial gain for the business and its clients.

Still, think Predictive Analytics is a bit confusing for you? SPIN is here to clear all your doubts.

Cyber attack! That’s the term that has possibly become a nightmare for businesses these days.

Time to control such exposed threats has stepped in. With a joint effort of technology and Cyber Security Programs, the avalanche of data making its way towards you can be managed.

Cyber attacks are prevalent and spare not a single sector that has an online presence.

The upsurge in dependency on networks, information, control systems. And the surge in the technological and organizational finesse of hackers boils down to only one thing- the higher risk of cyber attackers.

The number of sophisticated cyber attacks is rising. And the thriving role of vicious insiders in recent large-scale security breaches clearly indicate the need for data breach response plan.

Point to note- such a plan should offer more than a traditional approach and should actually keep up.

Time has changed

Change is prevalent, and cyber security concepts are no exception.

With time, the focus from safeguarding physical assets like stock or offices has shifted. Shifted to technology and software systems.
The primary motive behind this paradigm shift is to shield and go to bat for a business digital property.

Riding along with this transformational wave, companies have understood the need to re-strategize their cybersecurity. Analytics has emerged as the main bargaining chip when it comes to cyber resilience. All thanks to the persistent and highly advanced attacks.

And thanks to the adoption of Analytics, PDR (Prevent-Detect-Respond) has come to the picture. The below-mentioned bullet points will give a brief overview. This overview entails how cybersecurity analytics will bring the ball in your court.
• Detects infections, attacks, intrusions in seconds
• Transforms record of activity and volumes of raw unstructured data in meaningful actionable insights
• Gives an appropriate decision about the breach, its probable impact, and action to be taken.
• Instant response to detecting the infection, prevents data loss and averts outward intrusion.

How Big Data Analytics can help combat cyber data breach?

It is truly ironic that it is data, which is getting poached or stolen and it is only data that can put an end to such business ending breaches. All a business needs to do is to be able to use data in the right manner, and this process is called Big Data Analytics.

Here is a detailed summary of how such analytics can be the right fuel for cybersecurity programs. It can change the game for your business, and you can bid ‘TATA’ to online threats almost forever.

• Detect abnormality in device behaviorOff late, in many cases, it has been noticed that employee device is often used as the tool or podium to implant a Trojan horse. And eventually, lay hands on important data of the company.

The good news is, it can be stopped by incorporating Big Data into the system.

• Identify anomalies in the networkWith the help of Big Data, it is possible to find out the new lurking threats. If that’s not enough, Analytics correlates with the data available. This helps to draw a conclusion about the very nature of the attack.

• Analyses and identifies the network vulnerabilitiesOne of the most commendable approaches of Big Data Analytics is to devour the data. After that examine it and figure out which database has the customer identifying information and how prone it is to prevailing risks. Big data also shut the door on any potential source of risk for the online presence of a company.

Big Data Operationalization Benefits

Hard to admit, but it is true that identifying potential risks is not going to shun away the peril in question. It is imperative to derive the true value of Big Data insights to drive the required actions with relevant departments.

Being armed with operationalization capabilities, which can shift the data, locate the right signals and then drive the right action, is the need of the hour.

In tune with this, recently Oracle has waged a war against cyber threats with its Gen 2 Autonomous Cloud Infrastructure in a bid to ignite the fire of battling with cyber demons.

If you too are a victim of Cyber Threats and is convinced that only Big Data Analytics can come to your rescue, contact SPIN for your next move and provide the life-long security your organization deserves.

Let’s get down straight down to business- the potential of Artificial Intelligencehas toppled human imagination, and for most of the organizations, it has been the real game changer. That’s given!

In this competitive era, when surpassing your industry peers in the rat race is the need of the hour, Artificial Intelligence and Machine Learning can really seal the deal. Be it using Artificial Intelligence to figure out the buying trends, comprehend personalization, customize supply, comprehend customer behavior or conduct financial trading, embracing Artificial Intelligence has no other alternative.

So, to use Artificial Intelligence algorithms as the perfect Competitive Differentiator and up the game for your business, it goes without saying that one needs to harness this technology to line up the strategies, join forces and come up with potential opportunities.

Here is the Do’s a business needs to take on to leverage Artificial Intelligence and acquire that competitive edge, among its peers.

Executive sponsorship is vital for ARTIFICIAL INTELLIGENCE

The importance of the term ‘Executive Sponsorship’ has further garnered momentum with the introduction of Artificial Intelligence and Machine Learning. Why?

The explanation is simple- the more engaged the C-suite members are with this technology, the chances to implement and going down the line with Analytics and Artificial Intelligence application across the organization steps up.

As per market reports, enterprises that have successfully implemented Artificial Intelligence and Machine Learning at a large scale confirm the staggering contribution of C-suite executives, as compared to the organizations where Artificial Intelligence is not prevalent.

Align investments, assets, and business plans with ARTIFICIAL INTELLIGENCE strategy

If a business intends to be one step ahead of its adversaries then it needs to be on its toes. In tune with this, a business needs to set the tone of the organization’s investment, assets, and resources with the Artificial Intelligence application strategy.

To cut the long story short- to increase the pace of growth, it is imperative for a business to align enterprise priorities with Artificial Intelligence projects, and voila! Victory.

Implement Agile Methodology to boost the growth of ARTIFICIAL INTELLIGENCE and Analytics

It is a known fact that traditional IT development, often, takes longer than expected and sometimes yields unsatisfactory outcomes. To be precise, less business wins for your company.

Enters Agile methodology, which enables a business to access all data from the data warehouse and open doors for analytics insights, giving your business the competitive edge it needs.

ARTIFICIAL INTELLIGENCE to help your competitive future

Businesses these days are adapting and are open to ideas and technological advancements that can turn the tables for them. The promising future of Artificial Intelligence and Analytics makes it a preferred choice among business leaders to incorporate it in the company operations.

Bottom line- business organizations that will give Artificial Intelligence applications a strategic priority is most likely to acquire a competitive advantage in the marketplace.

If you are motivated to leverage Artificial Intelligence for your business, get in touch with SPIN and it team members today, who can help you with your journey.

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SPIN Strategy is laser-focused on client satisfaction and provides the solutions to maximize profits from different avenues of business, eventually retaining the majority of the customers. We employ our technical and domain knowledge to create solutions to cater to clients from a multitude of domains and sizes.